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1.
S Afr J Surg ; 59(4): 164-168, 2021 Dec.
Article de Anglais | MEDLINE | ID: mdl-34889540

RÉSUMÉ

BACKGROUND: Extralevator abdominoperineal excision (ELAPE) is a surgical technique that is indicated for low rectal cancer where sphincter preservation is not possible. Compared to conventional abdominoperineal excision major advantages of ELAPE are the risk reduction of intraoperative bowel perforation and positive circumferential margin which lead to a better oncological outcome. The aim of this study was to present our results in ELAPE surgery. METHODS: From February 2011 to February 2015, 40 patients underwent surgery for low rectal cancer at the Oncology Institute of Vojvodina. The collected data included sex, age, preoperative staging, neoadjuvant treatment, operative time, rate of intraoperative bowel perforation, rate of positive circumferential resection margins, histopathological analysis, postoperative mortality, tumour, node and metastasis (TNM) classification, local recurrence (LR) rate and presence of distant metastases. RESULTS: Positive circumferential margin was found in three (7.5%) patients while eight (20%) patients had intraoperative bowel perforation. LR during follow-up was seen in seven (17.5%) patients, three of them had intraoperative bowel perforation and two patients had positive circumferential margin. The estimated five-year cumulative incidence of LR is 7%. Distant metastases occurred in 18 (45%) patients. The estimated five-year survival rate is 62%.. CONCLUSION: The study shows satisfactory five-year survival rates of 62% in a highly complex patient group treated by ELAPE procedure.


Sujet(s)
Proctectomie , Tumeurs du rectum , Abdomen/chirurgie , Études de suivi , Humains , Périnée/chirurgie , Tumeurs du rectum/chirurgie , Résultat thérapeutique
2.
Hippokratia ; 22(1): 10-16, 2018.
Article de Anglais | MEDLINE | ID: mdl-31213752

RÉSUMÉ

BACKGROUND: In order to optimize the identification of persons with non-alcoholic fatty liver disease (NAFLD), several algorithms for hepatic steatosis were developed. These available algorithms, as well as an algorithm, derived using biochemical and anthropometric data of our participants, are compared in a cross-sectional pilot study. MATERIAL AND METHODS: We included 77 participants with abdominal obesity: 43 with NAFLD and 33 without NAFLD. Body mass index (BMI), waist circumference (WC) and hip circumference (HC), systolic and diastolic blood pressure were assessed. Fibrinogen, high sensitive C-reactive protein (hsCRP), aspartate aminotransferase (AST), alanine transaminase (ALT), gamma-glutamyl transferase (GGT), uric acid, ferritin, glucose, insulin, homocysteine, lipid status parameters, apolipoprotein A-I, apolipoprotein B and Lp(a)-lipoprotein were measured. Fatty liver was assessed by ultrasound with the presence or absence of hepatic steatosis. Discovering the most significant factor in the presence of NAFLD is assessed through logistic regression modeling. The predictor variables were chosen according to an algorithm derived from conducted factor analysis and other available algorithms for hepatic steatosis. RESULTS: Participants with NAFLD had significantly higher BMI (34.38 ± 9.73 vs 28.05 ± 4.79 kg/m2, p =0.001), WC (108.05 ± 11.47 vs 96.15 ± 14.27 cm, p =0.001), HC (114.93 ± 11.01 vs 108.21 ± 9.82 cm, p =0.050), systolic (128.98 ± 8.67 vs 122.42 ± 10.62 mmHg, p =0.010) and diastolic blood pressure (83.64 ± 5.94 vs 78.33 ± 7.57 mmHg, p =0.001), AST (23.93 ± 6.91 vs 21.70 ± 5.21 U/L, p =0.014), ALT (30.50 ± 13.70 vs 23.00 ± 11.75 U/L, p =0.007), hsCRP (4.34 ± 5.56 vs 2.98 ± 2.34mg/l, p =0.004) and uric acid (358.02 ± 83.29 vs 296.78 ± 84.54µmol/l, p =0.001), in comparison non NAFLD. Logistic regression model with algorithm derived from factor analysis showed the best performance. From other available algorithms, only fatty liver index (FLI) and hepatic steatosis index (HSI) had statistically significant discriminatory power.   Conclusions: Elevation of WC, HC, BMI, DBP, SBP, Fbg, hsCRP, glucose, and uric acid, incorporated in our hepatic steatosis prediction model, had the best predictive power among all assessed algorithms. HIPPOKRATIA 2018, 22(1): 10-16.

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